title: Data processing and analysis for protein microarrays.
abstract: Protein microarrays are a high-throughput technology capable of generating large quantities of proteomics data. They can be used for general research or for clinical diagnostics. Bioinformatics and statistical analysis techniques are required for interpretation and reaching biologically relevant conclusions from raw data. We describe essential algorithms for processing protein microarray data, including spot-finding on slide images, Z score, and significance analysis of microarrays (SAM) calculations, as well as the concentration dependent analysis (CDA). We also describe available tools for protein microarray analysis, and provide a template for a step-by-step approach to performing an analysis centered on the CDA method. We conclude with a discussion of fundamental and practical issues and considerations.
authors.affiliation: Cancer Vaccine Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
authors.forename: David S
authors.initials: DS
authors.lastname: DeLuca
authors.forename: Ovidiu
authors.initials: O
authors.lastname: Marina
authors.forename: Surajit
authors.initials: S
authors.lastname: Ray
authors.forename: Guang Lan
authors.initials: GL
authors.lastname: Zhang
authors.forename: Catherine J
authors.initials: CJ
authors.lastname: Wu
authors.forename: Vladimir
authors.initials: V
authors.lastname: Brusic
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D040081:Protein Array Analysis / Q000379:methods*; D012984:Software